---
_id: '13730'
abstract:
- lang: eng
  text: 'This paper introduces an LLM-mediated AI Advisor that contextualizes and
    synthesizes heterogeneous explainable AI (XAI) outputs to support fast and calibrated
    misinformation judgments in time-sensitive social media settings. We define LLM-mediated
    XAI as a process in which a large language model aggregates, prioritizes, and
    translates heterogeneous XAI outputs into a context-sensitive explanation tailored
    to the user’s decision situation. Semantic features, XAI modules and LLM-based
    summarization and synthesis enable the generation of explanations that are adapted
    in three ways: compressed for time-efficient decisions, translated into non-technical
    language, and progressively expandable for deeper inspection. Through a mixed-methods
    user study, including a quantitative study and a qualitative study, we analyze
    how users interpret, challenge and strategically rely on LLM-mediated explanations
    during real-world misinformation assessment tasks. The findings indicate that
    the approach reduces time-to-decision and supports critical inspection without
    inducing over-reliance. Progressive disclosure and different techniques to present
    information favored different user needs while conversational functionality was
    rarely used due to unclear benefits and fear of confusion.'
author:
- first_name: Valentin
  full_name: Grimm, Valentin
  id: '74000'
  last_name: Grimm
- first_name: Jessica
  full_name: Rubart, Jessica
  id: '45672'
  last_name: Rubart
  orcid: 0000-0003-0937-3551
- first_name: Eelco
  full_name: Herder, Eelco
  last_name: Herder
- first_name: Carsten
  full_name: Röcker, Carsten
  id: '61525'
  last_name: Röcker
citation:
  ama: 'Grimm V, Rubart J, Herder E, Röcker C. <i>LLM-Mediated XAI Explanations: An
    AI Advisor for Fast and Calibrated Judgments on Potential Misinformation</i>.
    (Balke WT, Plötzky F, Spaniol M, et al., eds.). ACM; 2026:110-116. doi:<a href="https://doi.org/10.1145/3795513.3810452">https://doi.org/10.1145/3795513.3810452</a>'
  apa: 'Grimm, V., Rubart, J., Herder, E., &#38; Röcker, C. (2026). LLM-Mediated XAI
    Explanations: An AI Advisor for Fast and Calibrated Judgments on Potential Misinformation.
    In W.-T. Balke, F. Plötzky, M. Spaniol, E. Herder, L. Manikonda, H. Liu, L.-D.
    Ibáñez, R. Rezapour, &#38; ACM Press (Eds.), <i>WebSci Companion ’26: Companion
    Publication of the 2026 18th ACM Web Science Conference</i> (pp. 110–116). ACM.
    <a href="https://doi.org/10.1145/3795513.3810452">https://doi.org/10.1145/3795513.3810452</a>'
  bjps: '<b>Grimm V <i>et al.</i></b> (2026) <i>LLM-Mediated XAI Explanations: An
    AI Advisor for Fast and Calibrated Judgments on Potential Misinformation</i>,
    Balke W-T et al. (eds). New York, USA: ACM.'
  chicago: 'Grimm, Valentin, Jessica Rubart, Eelco Herder, and Carsten Röcker. <i>LLM-Mediated
    XAI Explanations: An AI Advisor for Fast and Calibrated Judgments on Potential
    Misinformation</i>. Edited by Wolf-Tilo Balke, Florian Plötzky, Marc Spaniol,
    Eelco Herder, Lydia Manikonda, Haiming Liu, Luis-Daniel Ibáñez, Rezvaneh Rezapour,
    and ACM Press. <i>WebSci Companion ’26: Companion Publication of the 2026 18th
    ACM Web Science Conference</i>. New York, USA: ACM, 2026. <a href="https://doi.org/10.1145/3795513.3810452">https://doi.org/10.1145/3795513.3810452</a>.'
  chicago-de: 'Grimm, Valentin, Jessica Rubart, Eelco Herder und Carsten Röcker. 2026.
    <i>LLM-Mediated XAI Explanations: An AI Advisor for Fast and Calibrated Judgments
    on Potential Misinformation</i>. Hg. von Wolf-Tilo Balke, Florian Plötzky, Marc
    Spaniol, Eelco Herder, Lydia Manikonda, Haiming Liu, Luis-Daniel Ibáñez, Rezvaneh
    Rezapour, und ACM Press. <i>WebSci Companion ’26: Companion Publication of the
    2026 18th ACM Web Science Conference</i>. New York, USA: ACM. doi:<a href="https://doi.org/10.1145/3795513.3810452">https://doi.org/10.1145/3795513.3810452</a>,
    .'
  din1505-2-1: '<span style="font-variant:small-caps;">Grimm, Valentin</span> ; <span
    style="font-variant:small-caps;">Rubart, Jessica</span> ; <span style="font-variant:small-caps;">Herder,
    Eelco</span> ; <span style="font-variant:small-caps;">Röcker, Carsten</span> ;
    <span style="font-variant:small-caps;"><span style="font-variant:small-caps;">Balke,
    W.-T.</span> ; <span style="font-variant:small-caps;">Plötzky, F.</span> ; <span
    style="font-variant:small-caps;">Spaniol, M.</span> ; <span style="font-variant:small-caps;">Herder,
    E.</span> ; <span style="font-variant:small-caps;">Manikonda, L.</span> ; <span
    style="font-variant:small-caps;">Liu, H.</span> ; <span style="font-variant:small-caps;">Ibáñez,
    L.-D.</span> ; <span style="font-variant:small-caps;">Rezapour, R.</span> ; u. a.</span>
    (Hrsg.): <i>LLM-Mediated XAI Explanations: An AI Advisor for Fast and Calibrated
    Judgments on Potential Misinformation</i>. New York, USA : ACM, 2026'
  havard: 'V. Grimm, J. Rubart, E. Herder, C. Röcker, LLM-Mediated XAI Explanations:
    An AI Advisor for Fast and Calibrated Judgments on Potential Misinformation, ACM,
    New York, USA, 2026.'
  ieee: 'V. Grimm, J. Rubart, E. Herder, and C. Röcker, <i>LLM-Mediated XAI Explanations:
    An AI Advisor for Fast and Calibrated Judgments on Potential Misinformation</i>.
    New York, USA: ACM, 2026, pp. 110–116. doi: <a href="https://doi.org/10.1145/3795513.3810452">https://doi.org/10.1145/3795513.3810452</a>.'
  mla: 'Grimm, Valentin, et al. “LLM-Mediated XAI Explanations: An AI Advisor for
    Fast and Calibrated Judgments on Potential Misinformation.” <i>WebSci Companion
    ’26: Companion Publication of the 2026 18th ACM Web Science Conference</i>, edited
    by Wolf-Tilo Balke et al., ACM, 2026, pp. 110–16, <a href="https://doi.org/10.1145/3795513.3810452">https://doi.org/10.1145/3795513.3810452</a>.'
  short: 'V. Grimm, J. Rubart, E. Herder, C. Röcker, LLM-Mediated XAI Explanations:
    An AI Advisor for Fast and Calibrated Judgments on Potential Misinformation, ACM,
    New York, USA, 2026.'
  ufg: '<b>Grimm, Valentin u. a.</b>: LLM-Mediated XAI Explanations: An AI Advisor
    for Fast and Calibrated Judgments on Potential Misinformation, hg. von Balke,
    Wolf-Tilo u. a., New York, USA 2026.'
  van: 'Grimm V, Rubart J, Herder E, Röcker C. LLM-Mediated XAI Explanations: An AI
    Advisor for Fast and Calibrated Judgments on Potential Misinformation. Balke WT,
    Plötzky F, Spaniol M, Herder E, Manikonda L, Liu H, et al., editors. WebSci Companion
    ’26: Companion Publication of the 2026 18th ACM Web Science Conference. New York,
    USA: ACM; 2026.'
conference:
  end_date: 2026-05-26
  location: Braunschweig
  name: 18th ACM Web Science Conference ; WebSci Companion '26
  start_date: 2026-05-26
corporate_editor:
- ACM Press
date_created: 2026-05-05T16:16:34Z
date_updated: 2026-07-02T10:16:02Z
department:
- _id: DEP5023
- _id: DEP8008
- _id: DEP5027
doi: https://doi.org/10.1145/3795513.3810452
editor:
- first_name: Wolf-Tilo
  full_name: Balke, Wolf-Tilo
  last_name: Balke
- first_name: Florian
  full_name: Plötzky, Florian
  last_name: Plötzky
- first_name: Marc
  full_name: Spaniol, Marc
  last_name: Spaniol
- first_name: Eelco
  full_name: Herder, Eelco
  last_name: Herder
- first_name: Lydia
  full_name: Manikonda, Lydia
  last_name: Manikonda
- first_name: Haiming
  full_name: Liu, Haiming
  last_name: Liu
- first_name: Luis-Daniel
  full_name: Ibáñez, Luis-Daniel
  last_name: Ibáñez
- first_name: Rezvaneh
  full_name: Rezapour, Rezvaneh
  last_name: Rezapour
keyword:
- Large Language Model Mediation
- Explainable AI
- Decision Co- Pilot Systems
- Misinformation Detection
language:
- iso: eng
page: 110-116
place: New York, USA
publication: 'WebSci Companion ''26: Companion Publication of the 2026 18th ACM Web
  Science Conference'
publication_identifier:
  isbn:
  - 979-8-4007-2492-3
publication_status: published
publisher: ACM
quality_controlled: '1'
status: public
title: 'LLM-Mediated XAI Explanations: An AI Advisor for Fast and Calibrated Judgments
  on Potential Misinformation'
type: conference_editor_article
user_id: '89807'
year: '2026'
...
---
_id: '12383'
abstract:
- lang: eng
  text: Data stories are about revealing and communicating insights from complex data.
    In this paper, we propose conversational data stories, which support end users
    in understanding the key findings of the data analysis at hand by natural language
    conversation. Creating these stories manually means to put a lot of effort into
    understanding the data and crafting visuals. With increasingly powerful generative
    large language models (LLMs), natural language processing as well as automating
    the creation of data stories is a promising field. We present a concept for a
    conversational data storytelling system that integrates LLMs as well as explainable
    AI. We present the collected requirements for our system concept and how the requirements
    are addressed. To show the potential of our approach, we provide a use case scenario
    and a discussion in this paper. This is supposed to serve as a basis for future
    research that will aim at investigating the technical reliability and the user
    experience of such a system.
author:
- first_name: Valentin
  full_name: Grimm, Valentin
  id: '74000'
  last_name: Grimm
- first_name: Jessica
  full_name: Rubart, Jessica
  id: '45672'
  last_name: Rubart
  orcid: 0000-0003-0937-3551
- first_name: Patrick
  full_name: Söhlke, Patrick
  last_name: Söhlke
citation:
  ama: Grimm V, Rubart J, Söhlke P. <i>Conversational Data Stories</i>. (Atzenbeck
    C, Rubart J, ACM, eds.). ACM; 2024:6. doi:<a href="https://doi.org/10.1145/3679058.3688631">10.1145/3679058.3688631</a>
  apa: Grimm, V., Rubart, J., &#38; Söhlke, P. (2024). Conversational Data Stories.
    In C. Atzenbeck, J. Rubart, &#38; ACM (Eds.), <i>Proceedings of the 7th Workshop
    on Human Factors in Hypertext (HUMAN’24)</i> (p. 6). ACM. <a href="https://doi.org/10.1145/3679058.3688631">https://doi.org/10.1145/3679058.3688631</a>
  bjps: '<b>Grimm V, Rubart J and Söhlke P</b> (2024) <i>Conversational Data Stories</i>,
    Atzenbeck C, Rubart J, and ACM (eds). New York: ACM.'
  chicago: 'Grimm, Valentin, Jessica Rubart, and Patrick Söhlke. <i>Conversational
    Data Stories</i>. Edited by Claus Atzenbeck, Jessica Rubart, and ACM. <i>Proceedings
    of the 7th Workshop on Human Factors in Hypertext (HUMAN’24)</i>. New York: ACM,
    2024. <a href="https://doi.org/10.1145/3679058.3688631">https://doi.org/10.1145/3679058.3688631</a>.'
  chicago-de: 'Grimm, Valentin, Jessica Rubart und Patrick Söhlke. 2024. <i>Conversational
    Data Stories</i>. Hg. von Claus Atzenbeck, Jessica Rubart, und ACM. <i>Proceedings
    of the 7th Workshop on Human Factors in Hypertext (HUMAN’24)</i>. New York: ACM.
    doi:<a href="https://doi.org/10.1145/3679058.3688631">10.1145/3679058.3688631</a>,
    .'
  din1505-2-1: '<span style="font-variant:small-caps;">Grimm, Valentin</span> ; <span
    style="font-variant:small-caps;">Rubart, Jessica</span> ; <span style="font-variant:small-caps;">Söhlke,
    Patrick</span> ; <span style="font-variant:small-caps;">Atzenbeck, C.</span> ;
    <span style="font-variant:small-caps;">Rubart, J.</span> ; <span style="font-variant:small-caps;">ACM</span>
    (Hrsg.): <i>Conversational Data Stories</i>. New York : ACM, 2024'
  havard: V. Grimm, J. Rubart, P. Söhlke, Conversational Data Stories, ACM, New York,
    2024.
  ieee: 'V. Grimm, J. Rubart, and P. Söhlke, <i>Conversational Data Stories</i>. New
    York: ACM, 2024, p. 6. doi: <a href="https://doi.org/10.1145/3679058.3688631">10.1145/3679058.3688631</a>.'
  mla: Grimm, Valentin, et al. “Conversational Data Stories.” <i>Proceedings of the
    7th Workshop on Human Factors in Hypertext (HUMAN’24)</i>, edited by Claus Atzenbeck
    et al., ACM, 2024, p. 6, <a href="https://doi.org/10.1145/3679058.3688631">https://doi.org/10.1145/3679058.3688631</a>.
  short: V. Grimm, J. Rubart, P. Söhlke, Conversational Data Stories, ACM, New York,
    2024.
  ufg: '<b>Grimm, Valentin/Rubart, Jessica/Söhlke, Patrick</b>: Conversational Data
    Stories, hg. von Atzenbeck, Claus/Rubart, Jessica, ACM, New York 2024.'
  van: 'Grimm V, Rubart J, Söhlke P. Conversational Data Stories. Atzenbeck C, Rubart
    J, ACM, editors. Proceedings of the 7th Workshop on Human Factors in Hypertext
    (HUMAN’24). New York: ACM; 2024.'
conference:
  end_date: 2024-09-13
  location: Poznan Poland
  name: 7th Workshop on Human Factors in Hypertext (HUMAN)
  start_date: 2024-09-10
corporate_editor:
- ACM
date_created: 2025-01-21T13:23:17Z
date_updated: 2026-07-02T10:24:17Z
department:
- _id: DEP8008
doi: 10.1145/3679058.3688631
editor:
- first_name: Claus
  full_name: Atzenbeck, Claus
  last_name: Atzenbeck
- first_name: Jessica
  full_name: Rubart, Jessica
  id: '45672'
  last_name: Rubart
  orcid: 0000-0003-0937-3551
keyword:
- Data Storytelling
- Conversational Assistant
- Conversational Data Storytelling
- Explainable AI
language:
- iso: eng
page: '6'
place: New York
publication: Proceedings of the 7th Workshop on Human Factors in Hypertext (HUMAN'24)
publication_identifier:
  isbn:
  - 979-8-4007-1120-6
publication_status: published
publisher: ACM
status: public
title: Conversational Data Stories
type: conference_editor_article
user_id: '89807'
year: '2024'
...